Qrly charges an annual fee on your revenue, in marginal tranches like income tax — so there are no cliffs and the effective rate falls as you scale. Unlimited everything, one organisation, one installation. No per-seat licence, no per-query meter, no AI margin.
Three things a BI vendor can meter. Qrly meters exactly one of them, and it is the one that does not punish you for using the product.
The calculator runs exactly the tranche schedule published below it. Drag, type a figure, or pick a preset.
| Tier | Revenue | Annual | Monthly |
|---|---|---|---|
| Starter | up to €500k | €900 | €75 |
| Business | €1M | €1,500 | €125 |
| Scale | €5M | €3,600 | — |
| Scale+ | €25M | €9,000 | — |
| Enterprise | €100M | €21,750 | — |
| Group | €500M | €63,750 | — |
| Global | €1B | €93,750 | — |
Marginal rates, like income tax. Each rate applies only to the slice of revenue inside its own tranche.
| Revenue tranche | Marginal rate | Fee added by this tranche | Cumulative fee at the top |
|---|---|---|---|
| €0 – €500k | 0.18% | €900 | €900 |
| €500k – €1M | 0.12% | €600 | €1,500 |
| €1M – €5M | 0.0525% | €2,100 | €3,600 |
| €5M – €25M | 0.027% | €5,400 | €9,000 |
| €25M – €100M | 0.017% | €12,750 | €21,750 |
| €100M – €500M | 0.0105% | €42,000 | €63,750 |
| €500M+ | 0.006% | €30,000 per €500M | €93,750 at €1B |
The pricing metric is a product decision. It decides who is allowed to use the tool, and how often.
The point of a self-service BI platform is that the people closest to a decision can answer their own question. Per-seat licensing prices exactly that behaviour. Every additional viewer is a line item, so the rollout stops at the analysts, everyone else gets a screenshot pasted into a deck, and the platform quietly becomes a report factory with a queue.
Qrly has no seat count in its price. Users, groups, projects and collections are unlimited, permissions run from NO_ACCESS through VIEW, EXPLORE, CURATE and MANAGE on collections and NO_ACCESS / RESTRICTED / FULL on data, and none of those levels has a price attached. Adding the whole finance team on Monday changes nothing on the invoice.
Metered compute — per query, per credit, per capacity unit — is the single biggest cost driver in modern analytics, because the meter runs fastest exactly when the tool is working. A dashboard that auto-refreshes, a drill-down that someone actually explores, a scheduled report that fans out per region: all of it is billable, and so all of it becomes something to ration.
Qrly bills none of it. It also gives you the controls to keep your warehouse bill down rather than adding to it: four opt-in cache tiers (in-process, persistent, materialized tables written into a database you own, and full table sync with CDC), a per-connection query governor with a bounded concurrency semaphore and wait queue, and a per-user daily query budget that is checked and reserved atomically before every run.
Revenue per analytics user rises steeply with company size, so a flat percentage would break at both ends. The tranche schedule tapers instead: 0.18% on the first €500k, down through 0.12%, 0.0525%, 0.027%, 0.017% and 0.0105%, to 0.006% above €500M. A €1M business pays 0.15% of revenue; a €100M business pays 0.022%; a €1B business pays 0.009%.
Because the tranches are marginal, the curve is continuous. There is no band you can cross by one euro and re-price your entire turnover, and no renewal conversation that starts with a surprise.
Seat forecasts are guesses and query volumes are unknowable in advance, which is why analytics budgets are so consistently wrong. Your revenue, on the other hand, is a figure your finance team already produces, already forecasts and already signs off.
So the Qrly line in next year's budget is arithmetic rather than a negotiation, and it does not move when the platform succeeds. The one thing that ties the fee to the product is that the product is supposed to help the number it is priced on.
There is no feature matrix on this page because there is no feature matrix in the product. The list below is what a €900 customer gets and what a €93,750 customer gets.
| Capability | What ships | Tier |
|---|---|---|
| Connectivity | All 40 connection types — native engines plus AWS, Azure and GCP managed variants — over 12 dialect compilers | Every tier |
| Visual builder & QQL | Visual query builder, QQL with ~35 filter operators, joins, calculated fields, question-as-view, drill-down, and Monaco SQL with schema-aware autocomplete | Every tier |
| OLAP models | Star and snowflake models, ROLLUP / CUBE / GROUPING SETS, time-hierarchy drill, period-over-period, Top-N within group and pivot | Every tier |
| Dashboards | 12-column drag-and-drop grid, cascade filters, live dashboards over interval or Postgres LISTEN/NOTIFY, auto-refresh, morning briefing | Every tier |
| Reports | Card reports, Markdown analysis reports, report bursting, report packages, public share links, export to CSV, JSON, XML and XLSX | Every tier |
| Spreadsheet reports | A full workbook engine — roughly 500 worksheet functions, dynamic-array spilling, named ranges and live data bindings | Every tier |
| Alerts & subscriptions | Threshold alerts on any saved question, scheduled subscriptions on questions and dashboards, over email, Slack, webhook, SMS and an in-app inbox | Every tier |
| Embedding | Signed-JWT embed tokens with locked params, the JS SDK, the embeddable AI agent widget and public report share links — unlimited external viewers | Every tier |
| AI agent layer | Four personas — Analyst, Composer, Modeler, Investigator — on a ReAct runtime with propose-then-approve writes, and bring your own model | Every tier |
| MCP server | JSON-RPC at /mcp with SSE, 8 read-only tools, authenticated with the existing API tokens |
Every tier |
| Caching | All four tiers — JVM, persistent, materialized tables in a database you own, and table sync — all AES-256-GCM encrypted at rest | Every tier |
| Table sync & CDC | Full reload, watermark, snapshot-delta and CDC via embedded Debezium on Postgres, MySQL/MariaDB and SQL Server, with FK group coordination | Every tier |
| Constructions | Browser schema authoring compiled to dialect DDL behind a three-tier enablement cascade, with a SQL importer and plan preview | Every tier |
| Lineage & governance | Lineage graph across connections, tables, questions, dashboards, alerts and subscriptions; neighbourhood viewer; lineage report; verified questions; query audit log | Every tier |
| Whitelabel branding | Per-tenant and per-organisation logos, favicon, four theme colours and custom CSS, resolved field by field, plus a flag that hides Qrly attribution in embeds | Every tier |
| SSO | LDAP, Microsoft AD, Azure AD and Google OIDC — platform-wide and per-organisation registrations, with SSO discovery by hostname | Every tier |
| Public Data API | Data API v1 in JSON, CSV, NDJSON and Parquet, PostgREST-style RPC and table writes, scoped API tokens and the API explorer | Every tier |
| Self-hosting | On-premise or your own private cloud — Java 25 / Spring Boot 4 on PostgreSQL, GraalVM native-image capable, with an eight-step first-run wizard | Every tier |
| BCBS 239 module | All 14 Basel principles, a critical-data-element register, executable data-quality rules, column-level lineage and a signed-off risk-report catalogue | Every tier |
| Vendor support | Included with the licence at every tier — a named vendor in Belgium, not a community forum | Every tier |
The licence fee buys the software. Anything delivered by a person is a service, priced on its own and only when you ask for it — nothing is bundled into the fee that you would be paying for and not using.
Semantic and OLAP model design, QQL and dashboard structure, caching and table-sync strategy, permission and tenancy design, and reviews of an existing deployment. Scoped and quoted per engagement.
Deployment on your infrastructure, connection and driver configuration, identity provider setup, embedding integration, and migration of content from another BI tool where a rebuild is needed.
Administrator training, analyst sessions on the query builder and QQL, and workshops on the agent layer and embedding, remote or on site. Priced per session or per day.
None of this is required to run Qrly — it is designed to be installed and configured from the documentation. Where you do want help, it is available on request at additional cost, quoted before any work starts. Ask for a quote.
The licence is one line. The lines that usually sit underneath it are the reason analytics budgets drift.
Qrly never stands between you and the model provider. It does stand between the model provider and your budget.
You configure a per-organisation provider row with your own encrypted API key: Claude, OpenAI, Azure OpenAI (deployment-qualified), Gemini, Mistral, or a local Ollama, LM Studio, Jan.ai, LocalAI, GPT4All, LibreChat, Lobe Chat or Open WebUI endpoint. Any OpenAI-compatible service works out of the box, because the factory falls back to the OpenAI adapter for unknown types.
Point a local model at it and the marginal cost of an AI question is your own electricity. Nothing in the Qrly fee changes either way — the licence is a function of revenue, not of tokens.
The provider row carries the input and output cost per million tokens, the currency, the default model, a max-token cap and a budget period and amount. The admin AI providers page shows usage and spend charts against those figures, alongside a connection test and the org's security system prompt.
You get the accounting a resold-credits model gives you, without the margin that usually pays for it.
Agents are governed by a per-organisation daily token budget and a daily session cap — 50,000 tokens and 50 sessions a day by default — enforced as one of four independent stop conditions in the ReAct loop, alongside the step cap, a wall-clock deadline and provider errors. The budget is re-queried live mid-run so concurrent sessions cannot double-spend, with a pre-call check and a post-tool re-check on every iteration so a long run cannot overshoot by a whole turn.
A run that hits the ceiling ends as BUDGET_EXHAUSTED and says so, and budget state is surfaced to clients in the 429 response rather than failing silently.
Separately from AI, every user has a daily query budget — a per-user override falling back to an organisation default, and to 1,000 if neither is set. It is checked and reserved atomically before every query, race-safe via an upsert keyed on user and date, with bytes returned and AI tokens recorded asynchronously.
Administrators get a budget page with queries-today, active-user and over-budget KPIs, a date-ranged report and a per-user editor; users see their own budget on their profile. The per-connection query governor caps concurrency and queue depth on top, so a runaway dashboard cannot take a production database with it.
The fee is a percentage of your annual revenue, charged in marginal tranches like income tax: 0.18% on the first €500k, 0.12% from €500k to €1M, 0.0525% from €1M to €5M, 0.027% from €5M to €25M, 0.017% from €25M to €100M, 0.0105% from €100M to €500M and 0.006% above €500M.
Each rate applies only to the slice of revenue inside its tranche, so there are no cliffs, and a floor of €900 applies underneath — every customer up to €500k of turnover pays €900. A €1M business pays €1,500 a year; a €25M business pays €9,000; a €100M business pays €21,750. The absolute floor is €900 a year, and there is no free tier.
No. The fee is a function of your revenue and nothing else. Users, projects, collections, questions, dashboards, reports, alerts, subscriptions, embedded dashboards and embedded agent widgets are all unlimited.
Adoption never increases the bill, so there is no reason to ration logins, keep a viewer on a screenshot, or debate whether a colleague is worth a seat.
Flat bands create cliffs: one euro of extra revenue re-prices your entire turnover at the higher band. Marginal tranches work like income tax — each rate applies only to the slice of revenue inside its tranche — so the fee curve is continuous and the effective rate falls smoothly as you grow.
Crossing a tranche boundary is never an event, and the calculator above will show you exactly what a given growth scenario costs.
No. Every feature ships at every tier: all 40 connection types, the visual query builder and QQL, OLAP models, dashboards, reports, spreadsheet reports, alerts and subscriptions, embedding, the AI agent layer with bring-your-own-model, the MCP server, all four cache tiers, table sync and CDC, Constructions, lineage, whitelabel branding, SSO, the public Data API and self-hosting.
Qrly does not gate functionality behind price. The only thing that changes as your revenue grows is the fee.
Nothing on top of the model. Qrly is bring-your-own-LLM: you configure a per-organisation provider row — Claude, OpenAI, Azure OpenAI, Gemini, Mistral, or a local Ollama or LM Studio endpoint — with your own API key, and you pay that provider directly at their price.
Qrly meters the spend for you: input and output cost per million tokens and currency are recorded per provider and charted in the admin console, agent runs are capped by a daily token budget and a daily session budget with a live pre-call and post-tool re-check, and queries are capped by a per-user daily query budget. There is no AI usage margin because there is no AI usage line.
The minimum is €900 a year. Billing is annual, in euros only, excluding VAT, for one organisation and one installation, on-premise or in your own private cloud.
The published tiers from Starter at €900 through Global at €93,750 are simply the schedule evaluated at round revenue figures, with the €900 floor applied underneath — the calculator on this page runs the same tranche arithmetic.
Only if you want it. Qrly is built to be installed and configured from the documentation, and the licence fee covers the software. Consultancy, setup, migration and training are available on request at additional cost, scoped and quoted before any work starts.
Page updated 28 August 2026. All figures ex. VAT.
Tell us your revenue and we will tell you the fee — it is the same arithmetic the calculator on this page runs, and it does not change when you roll the platform out.